The success of cancer chemotherapy is dependent on both pharmacokinetic (PK) and pharmacodynamic (PD) processes that are often variable between patients. One consequence of this variability is that drug exposure is in some patients subtherapeutic, whereas in others exposure is sufficiently excessive to produce life-threatening toxicity. The research proposed here will develop and then examine the utility of population-based models characterizing drug responses as a means to improve patient therapy. Specifically, PK-PD models will be constructed to characterize myelosuppression - the dose-limiting toxicity induced by topoisomerase I inhibitors -based on data obtained in phase I clinical trials. Likewise, from other phase I patients, the effects of oltipraz, a chemopreventive agent, on the time-course of glutathione metabolism will be modeled. By describing patients as a group, rather than as individuals, these population models will yield the sources and extent of intrapatient and interpatient variability. By permitting better individualization of treatment through elucidation of how people vary, the results of these studies can enhance the effectiveness of cancer chemotherapy.